Research on Allocating Land Value-added Income Allocation in Pudong Land Reserve System Using Bootstrap-Elman Neural Network

Abstract

Abstract:

In the context of land storage and urban redevelopment, it is critical to purchase, store and make better use of inefficient urban land usage and the key lies in how to reasonably allocate the income from land value addition. In this paper, we first analyze the land value-added benefit distribution mechanism and put forward the idea that the value addition should satisfy the priority of payment of public and private interests and the ladder allocation method based on net income. Mathematical models are adopted for quantitative researches on Pudong district land increment income. The results show that the original property user shared ratio is 56.5% in the first rung while 45.6% in the second rung which is in line with the principal the government share higher proportion in upper rung. Priority of payment and ladder allocation method can realize the unification of fairness and efficiency, deepen the land value-added income allocation mechanism in theory and provide a basis for the government to innovate the revenue allocation in practice.

Key words: land purchase and storage, land value-added income, Bootstrap, Elman neural network

He Fang, Wang Xiaochuan, Zhang Hao. Research on Allocating Land Value-added Income Allocation in Pudong Land Reserve System Using Bootstrap-Elman Neural Network[J]. , 2015, 27(12): 57-64.

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